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Jackknife estimation of a cluster-sample IV regression model with many weak instruments

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  • Chao, John C.
  • Swanson, Norman R.
  • Woutersen, Tiemen

Abstract

This paper proposes new jackknife IV estimators that are robust to the effects of many weak instruments and error heteroskedasticity in a cluster sample setting with cluster-specific effects and possibly many included exogenous regressors. The estimators that we propose are designed to properly partial out the cluster-specific effects and included exogenous regressors while preserving the re-centering property of the jackknife methodology. To the best of our knowledge, our proposed procedures provide the first consistent estimators under many weak instrument asymptotics in the setting considered. We also present results on the asymptotic normality of our estimators and show that t-statistics based on said estimators are asymptotically normal under the null and consistent under fixed alternatives. Monte Carlo results show that our t-statistics perform better in controlling size in finite samples than those based on alternative jackknife IV procedures previously introduced in the literature.

Suggested Citation

  • Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    • Handle: RePEc:eee:econom:v:235:y:2023:i:2:p:1747-1769
    DOI: 10.1016/j.jeconom.2022.12.011
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    References listed on IDEAS

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    Cited by:

    1. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
    2. Anna Mikusheva & Liyang Sun, 2024. "Weak identification with many instruments," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages -28.
    3. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
    4. Johannes W. Ligtenberg & Tiemen Woutersen, 2024. "Multidimensional clustering in judge designs," Papers 2406.09473, arXiv.org.

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    More about this item

    Keywords

    Cluster sample; Instrumental variables; Heteroskedasticity; Jackknife; Many weak instruments; Panel data;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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